Back to search

Article

Towards mechanistic models of mutational effects: Deep Learning on Alzheimer’s Aβ peptide

2021-12-21

Abstract excerpt

<h4>ABSTRACT</h4> Alzheimer’s Disease (AD) is a debilitating form of dementia with a high prevalence in the global population and a large burden on the community and health care systems. AD’s complex pathobiology consists of extracellular β-amyloid deposition and intracellular hyperphosphorylated tau. Comprehensive mutational analyses can generate a wealth of knowledge about protein properties and enable crucial...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
db22db46-0ef1-5161-a48a-b0888e2c30f8
DOI
10.1101/2021.12.19.473403
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Towards mechanistic models of mutational effects: Deep Learning on Alzheimer’s Aβ peptideDOI 10.1101/2021.12.19.473403
Massive experimental quantification of amyloid nucleation allows interpretable deep learning of protein aggregationSemantic proximity
The genetic landscape for amyloid beta fibril nucleation accurately discriminates familial Alzheimer’s disease mutationsSemantic proximity
The genetic landscape for amyloid beta fibril nucleation accurately discriminates familial Alzheimer's disease mutations.Semantic proximity
An atlas of amyloid aggregation: the impact of substitutions, insertions, deletions and truncations on amyloid beta fibril nucleationSemantic proximity
An atlas of amyloid aggregation: the impact of substitutions, insertions, deletions and truncations on amyloid beta fibril nucleationSemantic proximity
Massively parallel genetic perturbation reveals the energetic architecture of an amyloid beta nucleation reactionSemantic proximity
Modeling mutational effects on biochemical phenotypes using convolutional neural networks: application to SARS-CoV-2Semantic proximity
USP-ddG: a unified structural paradigm with data efficacy and mixture-of-experts for predicting mutational effects on protein-protein interactions.Semantic proximity
Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition stateSemantic proximity
Conditioned Generative Modeling of Molecular Glues: A Realistic AI Approach for Synthesizable Drug-Like MoleculesSemantic proximity
Machine Learning on the Impacts of Mutations in the SARS-CoV-2 Spike RBD on Binding Affinity to Human ACE2 Based on Deep Mutational Scanning Data.Semantic proximity
Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networksSemantic proximity
Select a neighboring publication to make it the new centre.